Eric Godley

ABSTRACTAimFerns are globally distributed, yet the number of studies examining the historical evolution of African taxa is relatively low. Investigation of the evolution of African fern diversity is critical in order to understand patterns and processes that have global relevance (e.g., the pantropical diversity disparity [PDD] pattern). This study aims to examine when and from where a globally distributed fern lineage arrived in sub‐Saharan Africa, to obtain a better understanding of potential processes contributing to patterns of diversity across the region.LocationGlobal, sub‐Saharan Africa.TaxonAsplenium (Aspleniaceae).MethodsWe analysed five loci from 537 Asplenium taxa using a maximum likelihood (IQ‐Tree) phylogenetic framework. For age estimation, we performed penalised likelihood as implemented in treePL, and executed a Bayesian analysis using BEAST. Biogeographical analyses were carried out using BioGeoBEARS.ResultsMost dispersals into Africa occurred within the last ~55 myr, with the highest diversity of sub‐Saharan African taxa concentrated in two clades, each of which descended from an Asian ancestor. Additional dispersals to sub‐Saharan Africa can be found throughout the phylogeny. Lastly, potential cryptic species diversity exists within Asplenium as evidenced by several polyphyletic taxa.Main ConclusionsWe recover multiple dispersals of Asplenium to sub‐Saharan Africa, with two major lineages likely diversifying after arrival.

Climate change is reshaping forest ecosystems, presenting urgent and complex challenges that demand attention. In this context, research that quantifies interactions between climate and forests is substantial. However, modelling at a spatial resolution relevant for ecological processes presents a significant challenge, especially given the diverse geographical contexts in which it is applied. In our study, we aimed to assess the effects of applying CHELSA v.2.1 and WorldClim v2.1 data on bioclimatic analysis within the Río Puelo catchment area in northern Patagonia. To achieve this, we inter-compared and evaluated present and future bioclimates, drawing on data from both climate datasets. Our findings underscore substantial consistency between both datasets for temperature variables, confirming the reliability of both for temperature analysis. However, a strong contrast emerges in precipitation predictions, with significant discrepancies highlighted by minimal overlap in bioclimatic classes, particularly in steep and elevated terrains. Thus, while CHELSA and WorldClim provide valuable temperature data for northern Patagonia, their use for precipitation analysis requires careful consideration of their limitations and potential inaccuracies. Nevertheless, our bioclimatic analyses of both datasets under different scenarios reveal a uniform decline in mountain climates currently occupied by N. pumilio , with projections suggesting a sharp decrease in their coverage under future climate scenarios.

Aim Species occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.

Present-day geographic and phylogenetic patterns often reflect the geological and climatic history of the planet. Neontological distribution data are often sufficient to unravel a lineage’s biogeographic history, yet ancestral range inferences can be at odds with fossil evidence. Here, I use the fossilized birth–death process and the dispersal–extinction cladogenesis model to jointly infer the dated phylogeny and range evolution of the tree fern order Cyatheales. I use data for 101 fossil and 442 extant tree ferns to reconstruct the biogeographic history of the group over the last 220 million years. Fossil-aware reconstructions evince a prolonged occupancy of Laurasia over the Triassic–Cretaceous by Cyathealean tree ferns, which is evident in the fossil record but hidden from analyses relying on neontological data alone. Nonetheless, fossil-aware reconstructions are affected by uncertainty in fossils’ phylogenetic placement, taphonomic biases, and specimen sampling and are sensitive to interpretation of paleodistributions and how these are scored. The present results highlight the need and challenges of incorporating fossils into joint inferences of phylogeny and biogeography to improve the reliability of ancestral geographic range estimation.

Aim Species severely under‐represented in fossil pollen records leave gaps in interpretations and reconstructions of past vegetation. These ‘silent taxa’ leave little or no trace due to low pollen production, dispersal, preservation and taxonomic resolution. An approach for including them is through associating them with other species with reliable pollen representation. Here, we demonstrate a method for selecting such a proxy species for the Holocene using modern vegetation data.LocationNew Zealand.TaxonBeilschmiedia tawa (A.Cunn.) Benth. & Hook. F. ex Kirk (Lauraceae).MethodsWe used vegetation plot data to perform a pairwise co‐occurrence analysis of the New Zealand indigenous forest metacommunity to identify species with a strong positive association with Beilschmiedia tawa (tawa), a common tree severely under‐recorded in the pollen record. For those species, we then modelled their realised climatic niches to identify species with high niche overlap. We discuss how well those species could be interpreted from the Holocene fossil pollen record based on the representation of their pollen taxa.ResultsKnightia excelsa (rewarewa; Proteaceae) is a potential proxy for B. tawa in Holocene fossil pollen records, and other, range‐limited species may provide community‐specific proxies. We show combining resampling with sub‐sampling is a robust method for reducing the high false positive rate associated with large co‐occurrence analyses (1000+ sites) by limiting the sample size to 100 sites.Main ConclusionsWe show that the palaeoecology of silent taxa can be studied via proxy species, allowing their past distributions to be better understood. We highlight the importance of modelling many aspects of the realised niche to understand the usefulness and limitations of the silent–proxy association. Future research should focus on testing the underlying assumptions of the silent–proxy relationship so that models built on modern data can confidently be applied to palaeoecological data.

Predicting the likelihood that non-native species will be introduced into new areas remains one of conservation’s greatest challenges and, consequently, it is necessary to adopt adequate management measures to mitigate the effects of future biological invasions. At present, not much information is available on the areas in which non-native aquatic plant species could establish themselves in the Iberian Peninsula. Species distribution models were used to predict the potential invasion risk of (1) non-native aquatic plant species already established in the peninsula (32 species) and (2) those with the potential to invade the peninsula (40 species). The results revealed that the Iberian Peninsula contains a number of areas capable of hosting non-native aquatic plant species. Areas under anthropogenic pressure are at the greatest risk of invasion, and the variable most related to invasion risk is temperature. The results of this work were used to create the Invasion Risk Atlas for Alien Aquatic Plants in the Iberian Peninsula, a novel online resource that provides information about the potential distribution of non-native aquatic plant species. The atlas and this article are intended to serve as reference tools for the development of public policies, management regimes, and control strategies aimed at the prevention, mitigation, and eradication of non-native aquatic plant species.

Designing multispecies systems with suitable climatic affinity and identifying species' vulnerability under human‐driven climate change are current challenges to achieve successful adaptation of natural systems. To address this problem, we need to (1) identify groups of species with climatic similarity under climate scenarios and (2) identify areas with high conservation value under predicted climate change.To recognize species with similar climatic niche requirements that can be grouped for mixed cropping in Brazil, we employed ecological niche models (ENMs) and Spearman's ρ for overlap. We also used prioritization algorithms to map areas of high conservation value using two Shared Socioeconomic Pathways (SSP2‐4.5 and SSP5‐8.5) to assess mid‐term (2041–2060) and long‐term (2061–2080) climate change impacts.We identified 15 species groups with finer climatic affinities at different times depicted on hierarchical clustering dendrograms, which can be combined into agroecological agroforestry systems. Furthermore, we highlight the climatically suitable areas for these groups of species, thus providing an outlook of where different species will need to be planted over time to be conserved. In addition, we observed that climate change is predicted to modify the spatial association of these groups under different future climate scenarios, causing a mean negative change in species climatic similarity of 9.5% to 13.7% under SSP2‐4.5 scenario and 9.5% to 10.5% under SSP5‐8.5, for 2041–2060 and 2061–2080, respectively.Synthesis and applications. Our findings provide a framework for agroforestry conservation. The groups of species with finer climatic affinities identified and the climatically suitable areas can be combined into agroecological productive systems, and provide an outlook of where different species may be planted over time. In addition, the conservation priority zones displaying high climate stability for each species individually and all at once can be incorporated into Brazil's conservation plans by policymakers to prioritize specific sites. Lastly, we urge policymakers, conservation organizations and donors to promote interventions involving farmers and local communities, since the species' evaluated have proven to maintain landscapes with productive forest fragments and can be conserved in different Brazilian ecosystems.

Plants are a rich source of bioactive compounds and a number of plant-derived antiplasmodial compounds have been developed into pharmaceutical drugs for the prevention and treatment of malaria, a major public health challenge. However, identifying plants with antiplasmodial potential can be time-consuming and costly. One approach for selecting plants to investigate is based on ethnobotanical knowledge which, though having provided some major successes, is restricted to a relatively small group of plant species. Machine learning, incorporating ethnobotanical and plant trait data, provides a promising approach to improve the identification of antiplasmodial plants and accelerate the search for new plant-derived antiplasmodial compounds. In this paper we present a novel dataset on antiplasmodial activity for three flowering plant families – Apocynaceae, Loganiaceae and Rubiaceae (together comprising c. 21,100 species) – and demonstrate the ability of machine learning algorithms to predict the antiplasmodial potential of plant species. We evaluate the predictive capability of a variety of algorithms – Support Vector Machines, Logistic Regression, Gradient Boosted Trees and Bayesian Neural Networks – and compare these to two ethnobotanical selection approaches – based on usage as an antimalarial and general usage as a medicine. We evaluate the approaches using the given data and when the given samples are reweighted to correct for sampling biases. In both evaluation settings each of the machine learning models have a higher precision than the ethnobotanical approaches. In the bias-corrected scenario, the Support Vector classifier performs best – attaining a mean precision of 0.67 compared to the best performing ethnobotanical approach with a mean precision of 0.46. We also use the bias correction method and the Support Vector classifier to estimate the potential of plants to provide novel antiplasmodial compounds. We estimate that 7677 species in Apocynaceae, Loganiaceae and Rubiaceae warrant further investigation and that at least 1300 active antiplasmodial species are highly unlikely to be investigated by conventional approaches. While traditional and Indigenous knowledge remains vital to our understanding of people-plant relationships and an invaluable source of information, these results indicate a vast and relatively untapped source in the search for new plant-derived antiplasmodial compounds.

The debated vegetation response to climate change can be investigated through palynological fossil records from past extreme climate conditions. In this context, the early Eocene (53.3 to 41.2 million years ago (Ma)) is often referred to as a model for a greenhouse Earth. In the Xining Basin, situated on the North-eastern Tibetan Plateau (NETP), this time interval is represented by an extensive and well-dated sedimentary sequence of evaporites and red mudstones. Here we focus on the palynological record of the Early Eocene Climatic Optimum (EECO; 53.3 to 49.1 Ma) and study the fossil gymnosperm pollen composition in these sediments. In addition, we also investigate the nearest living relatives (NLR) or botanical affinity of these genera and the paleobiogeographic implications of their occurrence in the Eocene of the NETP. To reach our objective, we complemented transmitted light microscopy with laser scanning- and electron microscopy techniques, to produce high-resolution images, and illustrate the morphological variation within fossil and extant gymnosperm pollen. Furthermore, a morphometric analysis was carried out to investigate the infra- and intrageneric variation of these and related taxa. To place the data in context we produced paleobiogeographic maps for Phyllocladidites and for other Podocarpaceae, based on data from a global fossil pollen data base, and compare these with modern records from GBIF. We also assessed the climatic envelope of the NLR. Our analyses confirm the presence of Phyllocladidites (NLR Phyllocladus, Podocarpaceae) and Podocarpidites (NLR Podocarpus, Podocarpaceae) in the EECO deposits in the Xining Basin. In addition, a comparative study based on literature suggests that Parcisporites is likely a younger synonym of Phyllocladidites. Our findings further suggest that the Phyllocladidites specimens are derived from a lineage that was much more diverse than previously thought, and which had a much larger biogeographical distribution during the EECO than at present. Based on the climatic envelope of the NLR, we suggest that the paleoclimatic conditions in the Xining Basin were warmer and more humid during the EECO. We conclude that phylloclade-type conifers typical of the southern-temperate podocarp forests, had a northward geographical expansion during the EECO, followed by extirpation.

Aim Many invasive plant species benefit from enemy release resulting from the absence of insect herbivores in their invaded range. However, over time, specialized herbivores may ‘catch up’ with such invasive plants. Black locust is a tree species with a relatively limited native range in North America but has invaded large areas in virtually every temperate continent including North America. We hypothesize that both intra- and intercontinental spread of black locust leads to a parallel, though delayed pattern of intra- and intercontinental spread of insect herbivores. Location Global. Taxon Black locust, Robinia pseudoacacia, and its insect herbivores. Methods We compiled historical records of the occurrence of insect herbivore species associated with R. pseudoacacia from all world regions. Based on this list, we describe taxonomic patterns and investigate associations between environmental features and numbers of non-native specialist herbivores in the portion of North America invaded by R. pseudoacacia. Results A total of 454 herbivorous species are recorded feeding on R. pseudoacacia across the world, with 23 of these being specialized on Robinia. From this group, seven species have successfully expanded their range beyond North America. Within North America, the richness of specialists is explained by a combination of road density, R. pseudoacacia density, distance from the R. pseudoacacia native range, and climate. Main Conclusion Non-native herbivore species have accumulated on invasive R. pseudoacacia in both North America and in other continents. The steady build-up of invasions likely has diminished the enemy release that this invasive tree species has benefited from – a trend that will likely continue in the future. These findings support the hypothesis that invasive plants promote parallel though delayed invasions of specialist insect herbivores.